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Recent Advances in Feature Detectors and Descriptors: A Survey

Authors
Lee, HaeseongJeon, SemiYoon, InhyePaik, Joonki
Issue Date
Jun-2016
Publisher
대한전자공학회
Keywords
Keypoints; Feature detection; Feature description; Image matching; Invariant features; Computational cost
Citation
IEIE Transactions on Smart Processing & Computing, v.5, no.3, pp 153 - 163
Pages
11
Journal Title
IEIE Transactions on Smart Processing & Computing
Volume
5
Number
3
Start Page
153
End Page
163
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/8089
ISSN
2287-5255
Abstract
Local feature extraction methods for images and videos are widely applied in the fields of image understanding and computer vision. However, robust features are detected differently when using the latest feature detectors and descriptors because of diverse image environments. This paper analyzes various feature extraction methods by summarizing algorithms, specifying properties, and comparing performance. We analyze eight feature extraction methods. The performance of feature extraction in various image environments is compared and evaluated. As a result, the feature detectors and descriptors can be used adaptively for image sequences captured under various image environments. Also, the evaluation of feature detectors and descriptors can be applied to driving assistance systems, closed circuit televisions (CCTVs), robot vision, etc.
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첨단영상대학원 (영상학과)
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